Developing parallel algorithms for solving large-scale sparse linear systems is an important and challenging task in scientific computing and practical applications. In this talk, I will introduce the unsmoothed aggregation algebraic multigrid method for solving large-scale linear systems. I will give theoretical justifications of its optimality for model problems and its parallelization, especially on GPUs. Two different parallel approaches will be discussed and numerical results will be presented to demonstrate their efficiency.